Note
Go to the end to download the full example code.
Two-Dimensional Moment Frame Analysis¶
This is a complete example of frame analysis. Although it is a 2D case, it can be applied to more complex 3D models. While it demonstrates linear elastic analysis, it is also applicable to nonlinear elastoplastic analysis.
import matplotlib.pyplot as plt
import matplotlib.ticker as ticker
import numpy as np
import openseespy.opensees as ops
from matplotlib.colors import ListedColormap
import opstool as opst
import opstool.vis.pyvista as opsvis
Create the model¶
def FEModel():
ops.wipe()
ops.model("basic", "-ndm", 2, "-ndf", 3)
# Defining Nodes
ops.node(1, 0.000000e00, 0.000000e00)
ops.node(2, 3.600000e02, 0.000000e00)
ops.node(3, 7.200000e02, 0.000000e00)
ops.node(4, 0.000000e00, 1.620000e02)
ops.node(5, 3.600000e02, 1.620000e02)
ops.node(6, 7.200000e02, 1.620000e02)
ops.node(7, 0.000000e00, 3.240000e02)
ops.node(8, 3.600000e02, 3.240000e02)
ops.node(9, 7.200000e02, 3.240000e02)
ops.node(10, 0.000000e00, 4.800000e02)
ops.node(11, 3.600000e02, 4.800000e02)
ops.node(12, 7.200000e02, 4.800000e02)
ops.node(13, 0.000000e00, 6.360000e02)
ops.node(14, 3.600000e02, 6.360000e02)
ops.node(15, 7.200000e02, 6.360000e02)
ops.node(16, 0.000000e00, 7.920000e02)
ops.node(17, 3.600000e02, 7.920000e02)
ops.node(18, 7.200000e02, 7.920000e02)
ops.node(19, 0.000000e00, 9.480000e02)
ops.node(20, 3.600000e02, 9.480000e02)
ops.node(21, 7.200000e02, 9.480000e02)
ops.node(22, 0.000000e00, 1.104000e03)
ops.node(23, 3.600000e02, 1.104000e03)
ops.node(24, 7.200000e02, 1.104000e03)
# Write node restraint
ops.fix(1, 1, 1, 1)
ops.fix(2, 1, 1, 1)
ops.fix(3, 1, 1, 1)
# Define the rigidDiaphragm
ops.rigidDiaphragm(1, 5, 4, 6)
ops.rigidDiaphragm(1, 8, 7, 9)
ops.rigidDiaphragm(1, 11, 10, 12)
ops.rigidDiaphragm(1, 14, 13, 15)
ops.rigidDiaphragm(1, 17, 16, 18)
ops.rigidDiaphragm(1, 20, 19, 21)
ops.rigidDiaphragm(1, 23, 22, 24)
# Defining Frame Elements
ops.geomTransf("Linear", 1)
ops.element("elasticBeamColumn", 1, 1, 4, 7.230000e01, 2.950000e04, 3.230000e03, 1)
ops.element("elasticBeamColumn", 2, 4, 7, 7.230000e01, 2.950000e04, 3.230000e03, 1)
ops.element("elasticBeamColumn", 3, 7, 10, 7.230000e01, 2.950000e04, 3.230000e03, 1)
ops.element("elasticBeamColumn", 4, 10, 13, 6.210000e01, 2.950000e04, 2.670000e03, 1)
ops.element("elasticBeamColumn", 5, 13, 16, 6.210000e01, 2.950000e04, 2.670000e03, 1)
ops.element("elasticBeamColumn", 6, 16, 19, 5.170000e01, 2.950000e04, 2.150000e03, 1)
ops.element("elasticBeamColumn", 7, 19, 22, 5.170000e01, 2.950000e04, 2.150000e03, 1)
ops.element("elasticBeamColumn", 8, 2, 5, 8.440000e01, 2.950000e04, 3.910000e03, 1)
ops.element("elasticBeamColumn", 9, 5, 8, 8.440000e01, 2.950000e04, 3.910000e03, 1)
ops.element("elasticBeamColumn", 10, 8, 11, 8.440000e01, 2.950000e04, 3.910000e03, 1)
ops.element("elasticBeamColumn", 11, 11, 14, 7.230000e01, 2.950000e04, 3.230000e03, 1)
ops.element("elasticBeamColumn", 12, 14, 17, 7.230000e01, 2.950000e04, 3.230000e03, 1)
ops.element("elasticBeamColumn", 13, 17, 20, 6.210000e01, 2.950000e04, 2.670000e03, 1)
ops.element("elasticBeamColumn", 14, 20, 23, 6.210000e01, 2.950000e04, 2.670000e03, 1)
ops.element("elasticBeamColumn", 15, 3, 6, 7.230000e01, 2.950000e04, 3.230000e03, 1)
ops.element("elasticBeamColumn", 16, 6, 9, 7.230000e01, 2.950000e04, 3.230000e03, 1)
ops.element("elasticBeamColumn", 17, 9, 12, 7.230000e01, 2.950000e04, 3.230000e03, 1)
ops.element("elasticBeamColumn", 18, 12, 15, 6.210000e01, 2.950000e04, 2.670000e03, 1)
ops.element("elasticBeamColumn", 19, 15, 18, 6.210000e01, 2.950000e04, 2.670000e03, 1)
ops.element("elasticBeamColumn", 20, 18, 21, 5.170000e01, 2.950000e04, 2.150000e03, 1)
ops.element("elasticBeamColumn", 21, 21, 24, 5.170000e01, 2.950000e04, 2.150000e03, 1)
ops.element("elasticBeamColumn", 22, 4, 5, 4.710000e01, 2.950000e04, 5.120000e03, 1)
ops.element("elasticBeamColumn", 23, 7, 8, 4.710000e01, 2.950000e04, 5.120000e03, 1)
ops.element("elasticBeamColumn", 24, 10, 11, 3.830000e01, 2.950000e04, 4.020000e03, 1)
ops.element("elasticBeamColumn", 25, 13, 14, 3.830000e01, 2.950000e04, 4.020000e03, 1)
ops.element("elasticBeamColumn", 26, 16, 17, 3.250000e01, 2.950000e04, 3.330000e03, 1)
ops.element("elasticBeamColumn", 27, 19, 20, 3.250000e01, 2.950000e04, 3.330000e03, 1)
ops.element("elasticBeamColumn", 28, 22, 23, 3.250000e01, 2.950000e04, 3.330000e03, 1)
ops.element("elasticBeamColumn", 29, 5, 6, 4.710000e01, 2.950000e04, 5.120000e03, 1)
ops.element("elasticBeamColumn", 30, 8, 9, 4.710000e01, 2.950000e04, 5.120000e03, 1)
ops.element("elasticBeamColumn", 31, 11, 12, 3.830000e01, 2.950000e04, 4.020000e03, 1)
ops.element("elasticBeamColumn", 32, 14, 15, 3.830000e01, 2.950000e04, 4.020000e03, 1)
ops.element("elasticBeamColumn", 33, 17, 18, 3.250000e01, 2.950000e04, 3.330000e03, 1)
ops.element("elasticBeamColumn", 34, 20, 21, 3.250000e01, 2.950000e04, 3.330000e03, 1)
ops.element("elasticBeamColumn", 35, 23, 24, 3.250000e01, 2.950000e04, 3.330000e03, 1)
# Define the mass
ops.mass(5, 0.49, 0.0, 0.0)
ops.mass(8, 0.49, 0.0, 0.0)
ops.mass(11, 0.49, 0.0, 0.0)
ops.mass(14, 0.49, 0.0, 0.0)
ops.mass(17, 0.49, 0.0, 0.0)
ops.mass(20, 0.49, 0.0, 0.0)
ops.mass(23, 0.49, 0.0, 0.0)
FEModel()
Let’s first visualize the geometry by Pyvista:
opsvis.set_plot_props(line_width=4, point_size=2)
plotter = opsvis.plot_model(show_ele_numbering=True, show_node_numbering=True)
plotter.show()
You can also use the following code to visualize the model by using Plotly:
opst.vis.plotly.set_plot_props(line_width=4, point_size=2)
fig = opst.vis.plotly.plot_model()
fig
# fig.write_html("model.html")
# fig.show(renderer="browser")
Eigenvalue analysis¶
solver=”-fullGenLapack” is intended to extract all seventh-order modes. This solver should be avoided in actual large models.
opst.post.save_eigen_data(odb_tag="eigen", mode_tag=6, solver="-fullGenLapack")
WARNING - the 'fullGenLapack' eigen solver is VERY SLOW. Consider using the default eigen solver.Using DomainModalProperties - Developed by: Massimo Petracca, Guido Camata, ASDEA Software Technology
OPSTOOL™ :: Eigen data has been saved to G:\opstool\docs\.opstool.output/EigenData-eigen.zarr!
odb_tag = “eigen” is used to indentify the output database for eigenvalue analysis.
cmap = ListedColormap(["blue"])
opsvis.set_plot_props(cmap=cmap, line_width=4, point_size=5, font_size=12)
plotter = opsvis.plot_eigen(mode_tags=[1, 6], odb_tag="eigen", subplots=True, bc_scale=3, show_mp_constraint=False)
plotter.show() # for auto
OPSTOOL™ :: Loading eigen data from G:\opstool\docs\.opstool.output/EigenData-eigen.zarr ...
We can also retrieve the data of eigenvalue analysis:
model_props, eigen_vectors = opst.post.get_eigen_data(odb_tag="eigen")
model_props_df = model_props.to_pandas() # to pandas DataFrame
print(model_props_df.columns)
OPSTOOL™ :: Loading eigen data from G:\opstool\docs\.opstool.output/EigenData-eigen.zarr ...
Index(['eigenLambda', 'eigenOmega', 'eigenFrequency', 'eigenPeriod',
'partiFactorMX', 'partiFactorMY', 'partiFactorRMZ', 'partiMassMX',
'partiMassMY', 'partiMassRMZ', 'partiMassesCumuMX', 'partiMassesCumuMY',
'partiMassesCumuRMZ', 'partiMassRatiosMX', 'partiMassRatiosMY',
'partiMassRatiosRMZ', 'partiMassRatiosCumuMX', 'partiMassRatiosCumuMY',
'partiMassRatiosCumuRMZ'],
dtype='object', name='Properties')
print("Modal period: ", model_props_df["eigenPeriod"])
print("-" * 50)
print("Participation mass ratio: ", model_props_df["partiMassRatiosMX"])
print("-" * 50)
print("Cumulative participation mass ratio: ", model_props_df["partiMassRatiosCumuMX"])
Modal period: modeTags
1 1.273211
2 0.431278
3 0.242043
4 0.160179
5 0.118990
6 0.095064
Name: eigenPeriod, dtype: float64
--------------------------------------------------
Participation mass ratio: modeTags
1 79.962669
2 11.336182
3 4.180994
4 2.115029
5 1.414555
6 0.679967
Name: partiMassRatiosMX, dtype: float64
--------------------------------------------------
Cumulative participation mass ratio: modeTags
1 79.962669
2 91.298850
3 95.479845
4 97.594874
5 99.009429
6 99.689396
Name: partiMassRatiosCumuMX, dtype: float64
Static analysis¶
# Defining Lateral Distributed Loads:
FEModel()
# Define the load pattern
ops.timeSeries("Linear", 1)
ops.pattern("Plain", 1, 1)
ops.load(4, 2.5, 0.0, 0.0)
ops.load(7, 5.0, 0.0, 0.0)
ops.load(10, 7.5, 0.0, 0.0)
ops.load(13, 10.0, 0.0, 0.0)
ops.load(16, 12.5, 0.0, 0.0)
ops.load(19, 15.0, 0.0, 0.0)
ops.load(22, 20.0, 0.0, 0.0)
Re-examine the model:
opsvis.set_plot_props(line_width=4, point_size=4, font_size=12)
fig = opsvis.plot_model(show_nodal_loads=True, load_scale=2, bc_scale=3)
fig.show() # fig.show() for practical use
To perform the analysis:
n_steps = 10
ops.system("BandGeneral")
ops.constraints("Transformation")
ops.numberer("RCM")
ops.test("NormDispIncr", 1.0e-12, 10, 3)
ops.algorithm("Linear")
ops.integrator("LoadControl", 1 / n_steps)
ops.analysis("Static")
Save the results
odb = opst.post.CreateODB(odb_tag="static", interpolate_beam_disp=11)
for _ in range(n_steps):
ops.analyze(1) # one step of analysis
odb.fetch_response_step() # fetch the response on the current step
odb.save_response()
OPSTOOL™ :: All responses data with _odb_tag = static saved in
G:\opstool\docs\.opstool.output\RespStepData-static.odb!
Retrieve the nodal displacements:¶
node_resp = opst.post.get_nodal_responses(odb_tag="static")
print(
"Node 22 displacement in x direction: ",
node_resp["disp"].sel(nodeTags=22, DOFs="UX").data[-1],
)
OPSTOOL™ :: Loading all response data from G:\opstool\docs\.opstool.output\RespStepData-static.odb ...
Node 22 displacement in x direction: 1.450757
Retrieve element response:¶
ele_resp = opst.post.get_element_responses(odb_tag="static", ele_type="Frame")
print(ele_resp.data_vars)
OPSTOOL™ :: Loading Frame response data from G:\opstool\docs\.opstool.output\RespStepData-static.odb ...
Data variables:
basicDeformations (time, eleTags, basicDofs) float32 9kB 0.0 -0.0 ... 0.0
basicForces (time, eleTags, basicDofs) float32 9kB 0.0 -0.0 ... 0.0
localForces (time, eleTags, localDofs) float32 18kB -0.0 ... -527.7
plasticDeformation (time, eleTags, basicDofs) float32 9kB 0.0 -0.0 ... 0.0
sectionDeformations (time, eleTags, secPoints, secDofs) float32 65kB 0.0...
sectionForces (time, eleTags, secPoints, secDofs) float32 65kB -0....
sectionLocs (time, eleTags, secPoints, locs) float32 32kB 0.0 .....
ele_forces = ele_resp["sectionForces"]
print("M:", ele_forces.sel(eleTags=1, secDofs="MZ", secPoints=1).data)
print("V:", ele_forces.sel(eleTags=1, secDofs="VY", secPoints=1).data)
print("N:", ele_forces.sel(eleTags=1, secDofs="N", secPoints=1).data)
M: [ -0. 232.46773 464.93546 697.4032 929.8709 1162.3386
1394.8064 1627.274 1859.7418 2092.2095 2324.6772 ]
V: [ -0. -2.067208 -4.134416 -6.2016244 -8.268832 -10.3360405
-12.403249 -14.470457 -16.537664 -18.604874 -20.672081 ]
N: [-0. 6.9986734 13.997347 20.99602 27.994694 34.993366
41.99204 48.990715 55.989388 62.98806 69.98673 ]
Visualize node responses:¶
opsvis.set_plot_props(cmap="coolwarm", line_width=4, title_font_size=10)
plotter = opsvis.plot_nodal_responses(
odb_tag="static", resp_type="disp", resp_dof=["UX", "UY"], slides=True, defo_scale=100.0, interpolate_beam_disp=True
)
plotter.show()
OPSTOOL™ :: Loading responses data from G:\opstool\docs\.opstool.output\RespStepData-static.odb ...
Visualizing Element Response:¶
# Moment response
opsvis.set_plot_props(cmap="seismic", line_width=1, title_font_size=14)
opsvis.plot_frame_responses(
odb_tag="static",
resp_type="sectionForces",
resp_dof="Mz",
unit_symbol="N·mm",
unit_factor=1.0,
slides=True,
scale=-2.0,
style="wireframe",
).show()
OPSTOOL™ :: Loading responses data from G:\opstool\docs\.opstool.output\RespStepData-static.odb ...
Axial response
opsvis.plot_frame_responses(
odb_tag="static",
resp_type="sectionForces",
resp_dof="N",
slides=True,
scale=-2.0,
line_width=3,
style="wireframe",
).show()
OPSTOOL™ :: Loading responses data from G:\opstool\docs\.opstool.output\RespStepData-static.odb ...
Seismic response analysis¶
Load the ground motion data. All files can be downloaded here: click
gmdata = np.loadtxt("ELCENTRO.txt")
time = gmdata[:, 0]
accel = gmdata[:, 1]
print(len(time))
plt.plot(time, accel)
plt.show()
1560
Create the ground motion load pattern
FEModel()
ops.timeSeries("Path", 2, "-time", *time, "-values", *accel, "-factor", 386.4)
ops.pattern("UniformExcitation", 2, 1, "-accel", 2)
Create the Rayleigh damping
xDamp = 0.05
MpropSwitch = 1.0
KcurrSwitch = 0.0
KcommSwitch = 1.0
KinitSwitch = 0.0
nEigenI = 1 # mode 1
nEigenJ = 2 # mode 2
lambdaN = ops.eigen(nEigenJ) # eigenvalue analysis for nEigenJ modes
lambdaI = lambdaN[nEigenI - 1] # eigenvalue mode i
lambdaJ = lambdaN[nEigenJ - 1] # eigenvalue mode j
omegaI = np.sqrt(lambdaI)
omegaJ = np.sqrt(lambdaJ)
# M-prop. damping; D = alphaM*M
alphaM = MpropSwitch * xDamp * (2 * omegaI * omegaJ) / (omegaI + omegaJ)
# current-K; +beatKcurr*KCurrent
betaKcurr = KcurrSwitch * 2.0 * xDamp / (omegaI + omegaJ)
# last-committed K; +betaKcomm*KlastCommitt
betaKcomm = KcommSwitch * 2.0 * xDamp / (omegaI + omegaJ)
betaKinit = KinitSwitch * 2.0 * xDamp / (omegaI + omegaJ)
ops.rayleigh(alphaM, 0.0, 0.0, betaKcomm)
Perform analysis and save results
ops.wipeAnalysis()
ops.system("BandGeneral")
ops.constraints("Transformation")
ops.numberer("RCM")
ops.test("NormDispIncr", 1.0e-12, 10, 3)
ops.algorithm("Linear")
ops.integrator("HHT", 1.0, 0.5, 0.25)
ops.analysis("Transient")
n_steps, dt = 1600, 0.02
odb = opst.post.CreateODB(odb_tag="seismic", interpolate_beam_disp=11)
for _ in range(n_steps):
ops.analyze(1, dt)
odb.fetch_response_step()
odb.save_response()
# zlib=True to compress the data
OPSTOOL™ :: All responses data with _odb_tag = seismic saved in
G:\opstool\docs\.opstool.output\RespStepData-seismic.odb!
Retrieve Node Responses¶
node_resp = opst.post.get_nodal_responses(odb_tag="seismic")
node_disp22 = node_resp["disp"].sel(nodeTags=22, DOFs="UX")
node_vel22 = node_resp["vel"].sel(nodeTags=22, DOFs="UX")
node_accel22 = node_resp["accel"].sel(nodeTags=22, DOFs="UX")
OPSTOOL™ :: Loading all response data from G:\opstool\docs\.opstool.output\RespStepData-seismic.odb ...
fig, axes = plt.subplots(3, 1, sharex=True)
time = node_disp22.time
# Define colors and line styles
colors = ["#136ad5", "#fb8a2e"] # Use neutral colors for publication standards
line_styles = ["-", "--"] # Solid and dashed lines for differentiation
# Plot data with clear labels
axes[0].plot(time, node_disp22.data, color=colors[0], linestyle=line_styles[0], linewidth=1.5)
axes[1].plot(time, node_vel22.data, color=colors[0], linestyle=line_styles[0], linewidth=1.5)
axes[2].plot(time, node_accel22.data, color=colors[0], linestyle=line_styles[0], linewidth=1.5)
# Set axis labels and title font sizes
axes[0].set_ylabel("u", fontsize=10)
axes[1].set_ylabel("v", fontsize=10)
axes[2].set_ylabel("a", fontsize=10)
axes[2].set_xlabel("Time (s)", fontsize=10)
# Customize each subplot
for ax in axes:
ax.tick_params(axis="both", which="major", labelsize=8) # Set tick font size
ax.grid(True, linestyle="--", linewidth=0.5, alpha=0.7) # Add light grid lines
# ax.legend(fontsize=9, loc="best", frameon=False) # Simple legend without box
# Format X-axis ticks to have consistent significant figures
for ax in axes:
ax.xaxis.set_major_formatter(ticker.FormatStrFormatter("%.1f"))
# Adjust spacing between subplots
fig.subplots_adjust(hspace=0.2) # Adjust vertical spacing
# Save figure in a publication-friendly format
# plt.savefig("fig-node22resp.pdf", bbox_inches="tight")
plt.show()
print("OpenSees Node 22 Disp Max:", node_disp22.data.max())
print("OpenSees Node 22 Vel Max:", node_vel22.data.max())
print("OpenSees Node 22 Accel Max:", node_accel22.data.max())
print("-" * 50)
print("OpenSees Node 22 Disp Min:", node_disp22.data.min())
print("OpenSees Node 22 Vel Min:", node_vel22.data.min())
print("OpenSees Node 22 Accel Min:", node_accel22.data.min())
OpenSees Node 22 Disp Max: 4.886218
OpenSees Node 22 Vel Max: 24.562452
OpenSees Node 22 Accel Max: 284.1298
--------------------------------------------------
OpenSees Node 22 Disp Min: -4.141897
OpenSees Node 22 Vel Min: -25.271881
OpenSees Node 22 Accel Min: -249.5041
Retrieve Element Responses¶
ele_resp = opst.post.get_element_responses(odb_tag="seismic", ele_type="Frame", resp_type="sectionForces")
frame1Mz = -ele_resp.sel(eleTags=1, secDofs="MZ", secPoints=1)
frame1N = ele_resp.sel(eleTags=1, secDofs="N", secPoints=1)
frame1Vy = ele_resp.sel(eleTags=1, secDofs="VY", secPoints=1)
OPSTOOL™ :: Loading Frame sectionForces response data from
G:\opstool\docs\.opstool.output\RespStepData-seismic.odb ...
fig, axes = plt.subplots(3, 1, sharex=True)
time = frame1Mz.time
# Define colors and line styles
colors = ["#136ad5", "#fb8a2e"] # Use neutral colors for publication standards
line_styles = ["-", "--"] # Solid and dashed lines for differentiation
# Plot data with clear labels
axes[0].plot(time, frame1N.data, color=colors[0], linestyle=line_styles[0], linewidth=1.5)
axes[1].plot(time, frame1Vy.data, color=colors[0], linestyle=line_styles[0], linewidth=1.5)
axes[2].plot(time, frame1Mz.data, color=colors[0], linestyle=line_styles[0], linewidth=1.5)
# Set axis labels and title font sizes
axes[0].set_ylabel("N", fontsize=10)
axes[1].set_ylabel("V", fontsize=10)
axes[2].set_ylabel("M", fontsize=10)
axes[2].set_xlabel("Time (s)", fontsize=10)
# Customize each subplot
for ax in axes:
ax.tick_params(axis="both", which="major", labelsize=8) # Set tick font size
ax.grid(True, linestyle="--", linewidth=0.5, alpha=0.7) # Add light grid lines
# ax.legend(fontsize=9, loc="best", frameon=False) # Simple legend without box
# Format X-axis ticks to have consistent significant figures
for ax in axes:
ax.xaxis.set_major_formatter(ticker.FormatStrFormatter("%.1f"))
# Adjust spacing between subplots
fig.subplots_adjust(hspace=0.2) # Adjust vertical spacing
# Save figure in a publication-friendly format
# plt.savefig("fig-frame1-forces.pdf", bbox_inches="tight")
plt.show()
print("OpenSees Frame 1 N Max:", frame1N.data.max())
print("OpenSees Frame 1 Vy Max:", frame1Vy.data.max())
print("OpenSees Frame 1 Mz Max:", frame1Mz.data.max())
print("-" * 50)
print("OpenSees Frame 1 N Min:", frame1N.data.min())
print("OpenSees Frame 1 Vy Min:", frame1Vy.data.min())
print("OpenSees Frame 1 Mz Min:", frame1Mz.data.min())
OpenSees Frame 1 N Max: 233.99113
OpenSees Frame 1 Vy Max: 61.886253
OpenSees Frame 1 Mz Max: 6995.9204
--------------------------------------------------
OpenSees Frame 1 N Min: -196.78415
OpenSees Frame 1 Vy Min: -71.202286
OpenSees Frame 1 Mz Min: -8003.0625
Creating an .MP4 animation
opsvis.set_plot_props(font_size=8, title_font_size=10, line_width=5, point_size=3, cmap=["blue"])
plotter = opsvis.plot_nodal_responses_animation(
odb_tag="seismic",
resp_type="disp",
resp_dof=["UX", "UY"],
framerate=200, # Frames per second
savefig="NodalRespAnimation.gif", # or mp4
defo_scale=10.0,
interpolate_beam_disp=True,
)
plotter.close()
OPSTOOL™ :: Loading responses data from G:\opstool\docs\.opstool.output\RespStepData-seismic.odb ...
Animation has been saved to NodalRespAnimation.gif!
Total running time of the script: (2 minutes 9.919 seconds)